A Systematic Statistical Method of Solvent Selection for Optimal Separation in Liquid Chromatography

Optimization of resolution as a simultaneous function of solvent composition, pH and temperature in reversed-phase liquid chromatography

BACKGROUND

The latest chromatographic retention models are capable of accurately describe the dependencies of retention over a wide range of experimental conditions. By using a suitable conversion, these models can be transformed into equations expressing the optimization criteria as function of multiples variables. Even though that theoretical models significantly reduce the experimental requirements for optimizations, these models have been barely used. Instead, most optimizations rely on empirical exploration of the relationships between criterions and variables. There is a need for a strategy to reduce the required number of experiments in multivariated optimization of separations, and Fundamental Models offer a clear opportunity for addressing it.

RESULTS

A Fundamental Model is used to give the simultaneous dependence of chromatographic retention of seven ionizable pesticides on the three variables: solvent composition, temperature and pH (w, T, pH). Based on few experiments, the 10 parameters required to predict the chromatographic retention of those compounds, taken as model analytes, can be obtained. Two mathematical treatments to convert retentions into resolutions between pairs are used: one considering extracolumn dispersions and other neglecting these contributions. Using the Overlapped Resolutions Maps, extended to four dimensions, two optimal conditions can be found for the two different mathematical conversions. Chromatographic conditions were empirically evaluated obtaining the best results for the optimization considering extracolumn dispersions, proving that this condition is a true optimal. It was demonstrated that any small shift in any of the variables from this true optimal leads to a loss in resolution.

SIGNIFICANCE

Fundamental Models describing chromatographic retention as a simultaneous function of multiple variables are nowadays very accurate. In this work is demonstrated that these models are useful not only to predict retentions, but also to optimize separations, even in the more challenging mode: isocratic, isothermal and iso-pH. However, the success in the optimization procedure depends also on the proper definition of the mathematical conversion of the Fundamental Models into optimization criteria.

Behaviour of resolution by changing solvent strength and selectivity in the 'PRISMA' model using reversed-phase HPLC for biogenic amines

The retention behaviour of 17 dansylated biogenic amines in 6 linear gradients at 13 solvent combinations, expressed by the selectivity points (Ps) according to the 'PRISMA' model, was investigated. The dependence between the retention times (tr) and different gradients was examined. Three dimensional resolution (Rs) maps for each peak-pair in the different gradients at the 13 selectivity points were constructed, and the affect of the gradients on separation were investigated. The study showed that the dependence between the gradients and tr values of dansyl amides can be expressed using quadratic functions with a high degree of accuracy. These functions are well suited for estimating the resolution in different gradients and Ps. The three dimensional Rs maps clearly demonstrated the changes between the different gradients and Ps. This was of considerable benefit when searching the optimum mobile phase by changing both the solvent strength (ST) and selectivity.